JSON Expert

• Design, development, and productive rollout of an Enterprise HR Copilot based on Microsoft Copilot Studio to automate internal HR processes
• Development of an AI-supported assistant for answering employee inquiries based on a SharePoint knowledge base and internal company HR documentation
• Integration of the Copilot into Microsoft Teams, including welcome logic, user guidance, and role-based routing
• Automation of HR processes and approval workflows with Microsoft Power Automate to reduce manual processing steps
• Development of realistic HR documents and response templates with Azure OpenAI, taking business requirements and consistent company policies into account
• Implementation of prompt strategies, knowledge management, and response optimization to improve response quality and user acceptance
• Close collaboration with business departments to analyze requirements and integrate the AI solution into existing company processes

Technologies:

Microsoft Copilot Studio, Microsoft Teams, Azure OpenAI, SharePoint, Power Automate, Power Platform, Microsoft 365, Prompt Engineering, Workflow Automation

• Redesign of the company's BI infrastructure: replacement of a fragmented landscape of manually maintained Excel solutions and CSV imports with a centralized Power BI environment featuring a unified data model as the company-wide single source of truth
• Consolidation of previously isolated reporting logic into a central semantic model – eliminating redundant files, manual data transfers, and inconsistent metrics between departments
• Forecasting & planning: Design and implementation of company-wide liquidity planning in Power BI – from business logic to a fully automated, data-source-driven planning model replacing the previous manual Excel process; enables rolling forecasts and continuously up-to-date cash flow transparency for management
• Optimization of existing Power BI dashboards in terms of performance, structure, and analytical value using an AI-native approach
• Analysis and improvement of the data model, including data quality analyses, data cleansing, and consistent modeling using star schema, DAX, and Power Query
• Incident & anomaly analysis: Identification, investigation, and explanation of data anomalies, including root-cause analysis and concrete recommendations for action
• AI solution architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
• Creation of a historical data layer as a basis for trend and time-series analyses
• AI-supported automation: Design and development of AI skills, agents, loops, and processes for the automated analysis and interpretation of reports
• Automated reporting workflow: Setup of scheduled, automated email distribution of AI-generated analyses and recommendations to stakeholders
• Gathering and documentation of business requirements and coordination with business departments and IT as part of requirements engineering / product owner activities
• Breaking down overall requirements into clearly defined work packages and tasks
• Definition, prioritization, and management of milestones throughout the entire project lifecycle

Tools: POWER BI, M365, Copilot Studio, MIRO, Microsoft Business Central, Microsoft Fabric, Claude AI, ChatGPT, LangDock, MS VS Code

• Analysis of existing microservice structures and integration into the event-driven architecture
• Design and implementation of prototypes
• Introduction of structured workflows and integration into a solid testing strategy
• Team: Small specialized team (3-5 people) from analysis through implementation readiness
• Documentation of architectural decisions and definition of interfaces
• Integration of the event-driven pipeline into the existing landscape
• Technologies: Kafka, Docker, Microservices, Event-Driven Architecture, Java, Liquibase

• Built a scalable nearshore IT developer hub (Croatia, Czech Republic, Poland) as an independent company through a BOT model (Build – Operate – Transfer)
• Identified, selected, and managed full-service agencies; introduced management and control mechanisms, including KPIs, SLAs, and regular service reviews
• Prepared and reviewed data processing agreements and framework contracts in coordination with Legal & Compliance; integrated regulatory requirements (including KRITIS) into process design
• Advised on cloud vs. on-premise strategies, data storage, and authorization concepts; supported Procurement with tendering and service provider evaluations
• Managed change and process harmonization between internal teams and nearshore partners; reported to executive management, CFO, and CIO

Result: Scalable IT developer hub with an audit-ready governance model, reduced operating costs, and accelerated product development.

Design and implementation of a „unified-commerce“ platform for SMEs to sell and deliver multi-product bundles

Achievements: On-time design, delivery and customer acceptance of a 100% functional, CPQ-based „buy flow“ process for configuring and selling multi-product bundles within the specified timeframe of 90 days. Successfully tested integration of various interface services for the areas of: customer search, enrichment of customer data, address validation, service qualification, phone number validation, credit check, appointment selection and Quote-to-Order Transition.

Responsibilities:

• Strategic goal implementation: Derivation and implementation of strategic customer goals (e.g. release content, business value).
• Backlog Management: Creation and elaboration of backlog items (Initiatives, Epics, User Stories, Defects) in close coordination with the project team and customer.
• Prioritisation & Releases: Responsibility for prioritising the Product Backlog and implementing defined release goals.
• Deliverable Tracking: Tracking work results on the supplier and customer sides.
• Roadmap & Release Planning: Development and implementation of roadmaps and release plans together with the customer.
• Scope Responsibility: Responsibility for the contractually agreed scope of services.
• Claim Management: Active claim and change management towards the customer.
• Team Coordination: Management and coordination of the development team.
• Use of Synergies: Use of synergies between customer projects and product development.
• Proposal Preparation: Preparation of proposals (with supervision) and presentations on site at customer and partner locations.

Skills: Development, communication and implementation of product visions; Product Backlog Management; Stakeholder Management; Regular reporting to management and Steering Committees; Requirements analysis & Engineering; Conducting and documenting workshops; Functional leadership and coordination of (distributed) project teams and external service providers; Epic Management; User Story specifications; Creation of Use Cases, support with software testing and User Acceptance Testing (UAT); Release Management and Sprint Planning; Design of TO-BE processes; Process optimisation; Planning, design and specification of interfaces to existing and new systems; Identification, assessment and management of project risks; Active claim and change management; Facilitation of Sprint Planning and Reviews; Data migration; Scrum; Kanban; REST API; JSON; XML; BPMN; UML; Jira; Confluence

• New development and further development of the existing MS Dynamics CRM

IT systems: Microsoft Dynamics Customer Service, SharePoint, DevOps, SAP IS-U

• CRM implementation / further development
• Taking over from the previous service provider
• Business process analysis
• Agile project organization
• Business analysis / requirements engineering with AI support
• Use of AI in development
• Analysis of master data processes
• CRM customer data management
• Requirements documentation
• Stakeholder management
• Workshop moderation

Built an international e-commerce platform for a multi-vendor marketplace for digital assets from scratch. Designed and operated cloud native architectures at enterprise scale.

• Designed and operated a highly scalable microservice and serverless architecture
• Built the complete cloud infrastructure with Terraform + AWS CDK in AWS
• Provisioned ECS/EKS clusters (Fargate), Application Load Balancers (reverse proxy), and Lambda functions
• Observability & tracing with CloudWatch, DataDog, Prometheus, and Grafana
• End-to-end setup with DataDog (formerly AWS CloudWatch), Prometheus, and custom Grafana dashboards
• Integration of advanced metrics (including ORM mapper) and distributed tracing with Jaeger
• Robust backup and disaster recovery strategies
• RDS Postgres backups and hourly snapshots
• Read-only, asynchronously synchronized replicas with automated master failover in emergencies
• Minute-level rollback capability through versioned Docker images on ECS and Git-based CI/CD pipelines
• Created CI/CD pipelines with GitHub Actions for automated multi-stage deployments (Dev, Testing, Prod)
• Integrated Stripe for international payment processing
• Built a marketplace payment system with multiple parties and payout routines
• Used Algolia for high-performance real-time search of digital assets on the platform
• Federation of services with GraphQL and Hasura
• Later migration to GraphQL Mesh
• Test Driven Development (TDD) - unit, integration, and E2E testing with Jest, Vitest, and Playwright
• Used Next.js / React for modern frontend applications in the nx monorepo
• Enterprise security architecture & access control
• Integration of JWT tokens with Auth0, OAuth, OIDC, IP guards, BOLA protection, and secret vaults
• Authorization concepts with RBAC, ABAC, and native Postgres Row-Level Security (RLS)
• Built internal microfrontends with Retool for fast prototyping and operational business processes

Technologies: ABAC, AWS CDK, AWS CloudWatch, AWS ECS, AWS EKS, AWS Fargate, AWS RDS, AWS S3, Algolia, Auth0, DataDog, Docker, GitHub Actions, Grafana, GraphQL, GraphQL Mesh, Hasura, JWT, Jaeger, Java, JavaScript, Jest, Kotlin, Kubernetes, Monorepo, Next.js, OIDC, Playwright, Postgres, Postgres RLS, Prometheus, RBAC, Redis, Retool, Serverless, Stripe, Terraform, TypeScript, Vitest

• Analyzed, structured, and documented business requirements for digital investment solutions, such as robo-advisors.
• Designed applications for new retirement products, including user flows, UX requirements, and functional specifications.
• Modeled and optimized business processes and coordinated with stakeholders while taking regulatory requirements in the financial sector into account.

• Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
• GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
• AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner

• Overall responsibility for platform transformation across ERP, CRM, PIM and AI-supported process automation
• ERP transformation: Introduction and migration to Microsoft Dynamics 365 Business Central
• CRM & Growth Stack: Implementation of HubSpot as the central CRM and platform for lead and marketing automation
• Product data & Commerce Enablement: Introduction of an ePIM to scale Category Management and digital Commerce processes
• AI-supported process automation: Design and introduction of agent-based AI workflows to automate processes in Business Services, Accounting, Tender Management and Marketing
• Building a scalable platform organization consisting of Product Development, DevOps, UX, Cloud Engineering and Corporate IT
• Introduction of modern product and portfolio governance (e.g. OKRs, portfolio boards, value-based roadmaps) to manage technology-driven initiatives
• Harmonization of heterogeneous system landscapes and transformation into a modular, scalable platform architecture (ERP, CRM, PIM, integrated customer journeys)
• Coaching and development of Product Owners, Tech Leads, Delivery Managers and UX teams in building a scalable product organization

• As part of the project, the further development of the identity management system was driven forward. This included a comprehensive refactoring of the interfaces to the connected target systems. In addition, several special systems were successfully connected to the IAM to ensure end-to-end identity and authorization management.
• Technical design and solution proposals for IAM system development
• Requirements analysis and requirements management (IREB, BABOK)
• Alignment of the strategy with the future target architecture (TOGAF)
• Prototyping of solutions
• Documentation of requirements (Innovator)
• Analysis and documentation of requirements and creation of process models (UML, BPMN, ArchiMate)
• Modeling of requirements and system functionalities (OOA/OOD, UML)
• Further development of interfaces (SOAP, REST)
• Carrying out architecture reviews

• Recurring problem in my own AI-assisted projects: requirements analysis, use cases, and architecture decisions can be created quickly with AI support, but remain difficult to follow and scattered across Markdown files – knowledge is lost as soon as it is no longer in the context window. arknet turns requirements engineering and architecture knowledge into structured, verifiable data instead of plain text: requirements, use cases, and architecture decisions form a consistently linked knowledge graph, traceable from requirement to architecture decision – queryable by both people and AI agents. Technically based on RDF/OWL and a custom MCP server.

• Result: Working MCP daemon, Docker image published automatically to GHCR, nine hexagonal modules, eleven ADRs (including an Open-Core licensing model). Requirements engineering and Ubiquitous Language hexagons are active. Public as a Community Edition under Apache-2.0 since 07/2026 (github.com/kogn-io/arknet), together with the Claude Code plugin and GHCR image; Open-Core model.

• Label: Java, Maven, RDF, RDF4J, OWL, SPARQL, Model Context Protocol, Spring AI, Docker, GitHub, Git, Claude Code, Obsidian, DDD, Hexagonal Architecture, ArchUnit, JUnit, AssertJ, Interface Development, Software Architecture, Continuous Integration, Knowledge Management

• Led discovery phase and POC for Shopware to Shopify Plus migration across EMEA markets, evaluating platform suitability, technical architecture, and multi-brand/multi-country capabilities against business requirements.
• Designed reference architecture for Shopify Plus implementation incorporating headless front-end patterns (Vue.js, Nuxt.js), CMS integration (Magnolia), and Azure middleware (APIM, Functions, Logic Apps, Service Bus) for 11 EMEA markets.
• Defined migration strategy analyzing data mapping, cutover approach, and zero-downtime deployment patterns using Varnish caching, GitOps pipelines, and CI/CD orchestration across six vendor teams.
• Architected multi-tenant Shopify Plus governance model with centralized admin, localized storefront customization, and compliance controls (GDPR, data residency).
• Prototyped AI-driven search optimization (LLM.txt, JSON-LD) for product discoverability in Google AI results, demonstrating post-launch performance opportunities.
• Defined EMEA expansion roadmap for 15+ markets through C-level strategic workshops, identifying phased rollout, market-specific configurations, and resource requirements.
• Tech Stack: React, Nuxt.js, Vue.js, Magnolia CMS, Shopware, Shopify Plus, Azure (APIM, Functions, Logic Apps, Service Bus, Front Door), Varnish, SAP, MS Dynamics, Docker, Kubernetes, GitHub Actions, PostgreSQL, Kafka

AI telephone assistant platform

Claude Code, Google AI Studio, Python, LLM / Voice-AI, PostgreSQL

• Conception and hands-on development of an AI-supported telephone assistant platform (voice AI / LLM) – from idea and architecture to MVP/product.
• Built agentic workflows and full automations with Claude Code and Google AI Studio.
• Also delivered AI-supported work in client engagements: used Claude Code for governance documentation, requirement drafts, and automations.